In this project, we will analyze the performance of Major League Soccer Players.Our objective is to perform exploratory data analysis and statistical techniques to identify players with high-scoring potential, excellent playmaking skills, and efficient shooting. This analysis can be used for scouting purposes to identify promising players for recruitment.

The dataset contains data for all MLS players from 1996-2000 which consists of the following columns:

##  [1] "Player"  "Club"    "POS"     "GP"      "GS"      "MINS"    "G"      
##  [8] "A"       "SHTS"    "SOG"     "GWG"     "PKG.A"   "HmG"     "RdG"    
## [15] "G.90min" "SC."     "GWA"     "HmA"     "RdA"     "A.90min" "FC"     
## [22] "FS"      "OFF"     "YC"      "RC"      "SOG."    "Year"    "Season"

Some not so obvious abbreviations are GWG/GWA(game-winning goals/assists), HmG/RdG(home goals/road goals), and FC/FS(Fouls committed/Fouls sustained)

The dataset is first filtered to only include forwards and attacking midfielders. It’s clear several players have a shots on target percentage of right below 50% and it trends downwards. Hence, players who shoot over 50% can be considered top notch.

In the latest 5 years of the dataset, these are the top notch forwards who’ve scored at least 10 goals and maintained over 50% accuracy.

In soccer, you can’t score unless you have support from your teammates. That’s why some of the most sought after players are those who have the ability to both score and create goals

Only a handful players in the same 5 year period have the double of 10 goals and assists in a season.

Some goals happen to be more equal than others. If a team is losing drastically and a player scores a consolation, can that be weighed the same as a game winning one?

It can be argued that players who score winning goals are more valuable as they provide clutch moments

To create the clutch metric and display the frequency graph, we’ll also include game winning assists and follow these steps:

1. Calculate the clutch metric by summing the game winning goals (GWG) and assists (GWA), and dividing it by the total minutes played * 90 to get the clutch metric per 90 minutes.

2. Filter the players based on their positions (POS) as “M-F” and “F”.

3. Create a frequency graph to visualize the distribution of players based on the clutch metric.

It is clear that most forwards (or attacking midfielders) have a clutch metric of 0.30 or below. Clubs which target players who surpass that will have an advantage in tight matches.

##             Player Club Year clutch_metric
## 1   Jonathan Lewis  COL 2018     0.8219178
## 2      Diego Rubio  COL 2018     0.5761844
## 3  Anthony Fontana  PHI 2020     0.5304519
## 4   Jonathan Lewis  COL 2017     0.5263158
## 5   Tomas Conechny  POR 2019     0.5172414
## 6  Brandon Vazquez  CIN 2017     0.5056180
## 7    Raul Ruidiaz   SEA 2018     0.4918033
## 8    Saphir Taider  MTL 2020     0.4712042
## 9      Alan Pulido  SKC 2020     0.4677755
## 10     Niko Hansen  HOU 2017     0.4488778

These are the players with the highest clutch metric in a season (min. 10 games)

Only about 25 instances in a 5 year period of a player having such a high clutch metric.

It’s no secret players clubs will part ways with their players at the end of the season for various reasons including age, perceived value, lack of game time, etc.

These players who don’t renew a contract with their club become “free agents”. Normally clubs look at goals and assists count when assessing value. Players with counts high in those areas will generally be more expensive.

After the 2020 season, there were 32 free agents https://www.mlssoccer.com/news/complete-list-free-agents-2021-mls-season

Only 7 of the 32 even had a clutch moment the previous season !

A lot can be gained from playing around with data even in a volatile environment like sport. A manager could prefer players with a certain profile (like a clutch player) which can be found through analyzing pure statistics. There are already revolutionary data driven practices in baseball, and it’s only a matter of time before the difference is made in soccer as well.